Pattern recognition (PR) myoelectric control systems can dramatically improve an amputee patient's control of a powered prosthesis, but they still require that the user perform sequential movements to achieve a task. Coapt, LLC, is an early stage company that has initiated a controlled commercial release of PR myoelectric control for the benefit of upper-limb amputees. The controller is based on research completed by the Center for Bionic Medicine at the Rehabilitation Institute of Chicago (RIC) and has been widely developed and tested with transradial and higher-level amputees. Coapt has previously licensed valuable PR controller technology and intellectual property from the RIC. We now seek to extend this work to allow for simultaneous, rather than sequential, control of movements. The result will be an intuitive to use prosthesis that generates fluid and like- life movements. The long-term goal is to provide upper-limb amputees with a more intuitive option for controlling their externally powered prostheses. The objective of this application is to extend our control system to allow for intuitive control of simultaneous movements. We will achieve this by creating an innovative, individual specific model that will automatically generate simultaneous movement data from a set if discrete movement data. As a result, the system will be easy to train with our existing prosthesis guided training framework, and will work across a variety of sites and manufactures with minimal on-site engineering time. The application comprises the following two specific aims: (1) develop a viable and clinically focused training routine for simultaneous control; and (2) evaluate simultaneous control performance in a virtual environment. Under the first aim, we will test a model to automatically generate electromyographic (EMG) signals corresponding to simultaneous movements using only EMG data that we already collect as part of our patient accepted prosthesis guided training calibration routine. Under the second aim, we will evaluate the patients' performances using simultaneous control in virtual environment during a Fitts' Law style task and compare the results to those achieved using sequential PR. The proposed research is significant because it addresses specific patient identified needs and has a pathway to rapid clinical deployment. Ultimately, this research will help upper-limb amputees to dramatically improve the control of their prostheses, allowing for an improved quality of life and promote return to work in many cases.